Identification of Mir-9 in Glioma Diagnosis and Prognosis

Tian, Fengxuan; Ma, Haifeng; Zhang, Qing

doi:10.7754/clin.lab.2019.190914

Cited by 7 publications

(3 citation statements)

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“…Proteomic approaches could identify new biomarkers for the glioma prognosis. Indeed, mRNA, lncRNA, or circRNA can be biomarkers for predicting glioma survival time in many studies (10)(11)(12), however, dysregulation of mRNA expression in gliomas does not equate to corresponding protein products as tumor markers, because mRNA expression is poorly correlated with protein levels (13). Even if the VEGF and some angiogenesis-related proteins, extracellular matrix proteins, matrix metalloproteinases, glial brillary acidic protein (GFAP), macrophage migration inhibitory factor (MIF), and function-associated proteins are made to glioblastoma protein markers in several studies (14), single protein exhibit markedly insu cient speci city and sensitivity.…”

Section: Introductionmentioning

confidence: 99%

Proteomics‑based prognostic signature predicts prognosis and immunity in glioma

Shen

Zhou

Tan

et al. 2023

Preprint

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The prognosis of glioma patients is closely associated with the expression of immune cells and oncoproteins. Therefore, protein-related signatures were conducted to improve the prediction of overall survival (OS) in glioma patients after surgery. Differential oncoproteins were selected from the Renji cohort and The Cancer Genome Atlas (TCGA) database. The least absolute shrinkage and selection operator (LASSO) regression model is designed to construct the multiple oncoprotein model related to OS in two test series. Furthermore, the 6-oncoprotein model was tight associated with immune cell infiltration, immune function, and immunotherapy. In summary, the 6-oncoprotein marker, a favorable biomarker for the prognosis and immune characteristics of glioma, could help individualized immunotherapy for patients with glioma.

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Section: Introductionmentioning

confidence: 99%

Proteomics‑based prognostic signature predicts prognosis and immunity in glioma

Shen

Zhou

Tan

et al. 2023

Preprint

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“…The dose of the first two treatment methods needs to be strictly controlled, and there will be some damage to normal tissues, which is greatly limited in the treatment of glioma [ 20 ]. Therefore, surgical treatment is the most commonly used and effective treatment of glioma in clinics [ 21 ]. Gliomas with a low degree of deterioration are mostly cured by surgery, while gliomas with a high degree of deterioration can greatly prolong the life span of patients by surgical treatment.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence Algorithm‐Based Intraoperative Magnetic Resonance Navigation for Glioma Resection

Wei

Zhang

et al. 2022

Contrast Media & Molecular Imaging

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The study aimed to analyze the application value of artificial intelligence algorithm-based intraoperative magnetic resonance imaging (iMRI) in neurosurgical glioma resection. 108 patients with glioma in a hospital were selected and divided into the experimental group (intraoperative magnetic resonance assisted glioma resection) and the control group (conventional surgical experience resection), with 54 patients in each group. After the resection, the tumor resection rate, NIHSS (National Institute of Health Stroke Scale) score, Karnofsky score, and postoperative intracranial infection were calculated in the two groups. The results revealed that the average tumor resection rate in the experimental group was significantly higher than that in the control group (P < 0.05). There was no significant difference in Karnofsky score before and after the operation in the experimental group (P > 0.05). There was no significant difference in NIHSS score between the experimental group and the control group after resection (P > 0.05). The number of patients with postoperative neurological deficits in the experimental group was smaller than that in the control group. In addition, there was no significant difference in infection rates between the two groups after glioma resection (P > 0.05). In summary, intraoperative magnetic resonance navigation on the basis of a segmentation dictionary learning algorithm has great clinical value in neurosurgical glioma resection. It can maximize the removal of tumors and ensure the integrity of neurological function while avoiding an increased risk of postoperative infection, which is of great significance for the treatment of glioma.

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“…Therefore, the exploration of biomarkers related to the occurrence and progression of glioma can provide a new direction for its accurate treatment [ 13 ]. Microribonucleic acid miR-296and miR-517c are a class of endogenous noncoding single-stranded small molecules RNA, which can bind to mRNA to block the expression of protein-coding genes and participate in the regulation of a variety of physiological and pathological functions [ 14 ]. Studies have shown that serum miR-296 and miR-517c are abnormally expressed in breast cancer, colorectal cancer, prostate cancer, and other malignant tumors and are closely related to the occurrence and development of these malignant tumors.…”

Section: Introductionmentioning

confidence: 99%

The Value of miR-296 and miR-517c in Evaluating the Prognosis of Patients with Glioma after Radiotherapy and Chemotherapy

Wang

Shi

Lei

et al. 2021

Journal of Oncology

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Objective. To explore the value of miR-296 and miR-517c in evaluating the prognosis of patients with glioma after radiotherapy and chemotherapy. Methods. 732 patients with glioma were selected from January 2012 to January 2018. According to the effect of postoperative chemotherapy, the patients were divided into two groups: the effective group and the ineffective group. The serum miR-296, miR-517c, and clinicopathological parameters of the two groups before chemotherapy were compared. The factors affecting the sensitivity of radiotherapy and chemotherapy and the predictive efficacy of miR-296 and miR-517c on the prognosis of patients were analyzed. Results. The expression level of miR-296 in glioma tissue was significantly correlated with tumor pathological grade and depth of invasion ( P < 0.05 ), and the expression level of miR-296 in glioma tissue was significantly correlated with tumor pathological grade ( P < 0.05 ). Logistic regression analysis showed that tumor size, WHO grade, and serum miR-296 and miR-517c levels were all factors affecting chemosensitivity ( P < 0.05 ). The sensitivity, specificity, accuracy, and AUC of serum miR-296 prediction were 76.95%, 89.64%, 85.35%, and 0.891, respectively. The sensitivity, specificity, accuracy, and AUC of serum miR-517c prediction were 72.81%, 86.50%, 82.19%, and 0.739, respectively. Conclusion. miR-296 and miR-517c are closely related to the chemosensitivity and prognosis of glioma patients. High levels of miR-296 and miR-517c can enhance chemosensitivity and serve as reliable indexes to predict the prognosis of patients with glioma.

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Identification of Mir-9 in Glioma Diagnosis and Prognosis

Cited by 7 publications

References 0 publications

Proteomics‑based prognostic signature predicts prognosis and immunity in glioma

Proteomics‑based prognostic signature predicts prognosis and immunity in glioma

Artificial Intelligence Algorithm‐Based Intraoperative Magnetic Resonance Navigation for Glioma Resection

The Value of miR-296 and miR-517c in Evaluating the Prognosis of Patients with Glioma after Radiotherapy and Chemotherapy

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